Estimation of sand and gravel extraction sites

Measurable value optimization is suggested as a method of integrating ecological concerns into the planning and management of offshore sand and gravel mining.

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GEOLOGIC CONTEXTS OF MINNESOTA’S SAND AND GRAVEL PITS

10.1130/abs/2020nc-348179 ◽

2020 ◽

Author(s):

Greg Brick ◽

Keyword(s):

Gravel Pits ◽

Sand And Gravel

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Transport of Microorganisms in the Underground – Processes, Experiments and Simulation Models

Water Science & Technology ◽

10.2166/wst.1991.0080 ◽

1991 ◽

Vol 24 (2) ◽

pp. 309-314 ◽

Cited By ~ 16

Author(s):

G. Teutsch ◽

K. Herbold-Paschke ◽

D. Tougianidou ◽

T. Hahn ◽

K. Botzenhart

Keyword(s):

Simulation Models ◽

Mass Conservation ◽

Breakthrough Curves ◽

Conservation Equation ◽

Retardation Factor ◽

Natural Systems ◽

Laboratory Setup ◽

Preliminary Model ◽

Sand And Gravel ◽

Mass Conservation Equation

In this paper the major processes governing the persistence and underground transport of viruses and bacteria are reviewed in respect to their importance under naturally occurring conditions. In general, the simulation of the governing processes is based on the macroscopic mass-conservation equation with the addition of some filter and/or retardation factor and a decay coefficient, representing the natural “die-off” of the microorganisms. More advanced concepts try to incorporate growth and decay coefficients together with deposition and declogging factors. At present, none of the reported concepts has been seriously validated. Due to the complexity of natural systems and the pathogenic properties of some of the microorganisms, experiments under controlled laboratory conditions are required. A laboratory setup is presented in which a great variety of natural conditions can be simulated. This comprises a set of 1 metre columns and an 8 metre stainless-steel flume with 24 sampling ports. The columns are easily filled and conditioned and therefore used to study the effects of different soil-microorganism combinations under various environmental conditions. In the artificial flume natural underground conditions are simulated using sand and gravel aquifer material from the river Neckar alluvium. A first set of results from the laboratory experiments is presented together with preliminary model simulations. The large variety of observed breakthrough curves and recovery for the bacteria and viruses under investigation demonstrates the great uncertainty encountered in microbiological risk assessment.

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Statistical Law and Predictive Analysis of Compressive Strength of Cemented Sand and Gravel

Science and Engineering of Composite Materials ◽

10.1515/secm-2020-0030 ◽

2020 ◽

Vol 27 (1) ◽

pp. 291-298

Author(s):

Shoukai Chen ◽

Yongqiwen Fu ◽

Lei Guo ◽

Shifeng Yang ◽

Yajing Bie

Keyword(s):

Compressive Strength ◽

Back Propagation ◽

Back Propagation Neural Network ◽

Predictive Analysis ◽

Distribution Law ◽

Data Set ◽

Cemented Sand ◽

Mix Proportion ◽

Kolmogorov Smirnov ◽

Sand And Gravel

AbstractA data set of cemented sand and gravel (CSG) mix proportion and 28-day compressive strength was established, with outliers determined and removed based on the Boxplot. Then, the distribution law of compressive strength of CSG was analyzed using the skewness kurtosis and single-sample Kolmogorov-Smirnov tests. And with the help of Python software, a model based on Back Propagation neural network was built to predict the compressive strength of CSG according to its mix proportion. The results showed that the compressive strength follows the normal distribution law, the expected value and variance were 5.471 MPa and 3.962 MPa respectively, and the average relative error was 7.16%, indicating the predictability of compressive strength of CSG and its correlation with the mix proportion.

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